Hey doc, is that your stethoscope?

Coovert, Sally A.; Ducey, Adam J.; Grichanik, Mark; Coovert, Michael D.; Nelson, Robert M.

doi:10.1145/2141512.2141545

Cited by 2 publications

References 3 publications

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Monitoring motor symptoms in Parkinson’s disease via instrumenting daily artifacts with inertia sensors

Tian

Fan

et al. 2019

CCF Trans. Pervasive Comp. Interact.

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Daily monitoring of Parkinson's disease is important since clinical assessments can only provide a brief and limited view of a patient's condition. However, traditional approaches rely heavily on patients' self-reports or diaries, which are subjective and often lack of necessary details. In this work, we instrument a handle that can be attached to cutlery with inertial sensors to collect motion data unobtrusively. By analyzing the data of patients and normal people collected in the clinic, we demonstrated that our machine learning based model can not only distinguish between patients and normal people, but also identify the disease levels in a fine-grained manner. To further understand how the self-tracking data is used in clinic, we conducted a semi-structured interview with several clinicians. Through the interpretation from the perspective of both physicians and patients, we found that our handle can help the physicians better understand disease progression and promote patients' engagement in tackling the disease.

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Monitoring motor symptoms in Parkinson’s disease via instrumenting daily artifacts with inertia sensors

Tian

Fan

et al. 2019

CCF Trans. Pervasive Comp. Interact.

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Shewbridge

Powell

et al. 2015

Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems

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The purpose of this study is to address the use of movement assessment sensors for clinical diagnosis and treatment. Eleven patients with Parkinson's disease who had undergone deep brain stimulation (DBS) surgery were observed during follow-up appointments for adjustments to the stimulation settings. We examine the ways in which the patients and clinicians assess movement ability together in the clinic and how these assessments relate to the treatment of functional disability through DBS. We have found that effective assessment of movement and treatment efficacy is a collaborative and interpretive process (co-interpretation) that relies on input from patients, clinicians, and caregivers. From these findings we describe the design directions for movement sensors to support co-interpretation of movement in a clinical context as opposed to simply movement definition.

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Hey doc, is that your stethoscope?

Cited by 2 publications

References 3 publications

Monitoring motor symptoms in Parkinson’s disease via instrumenting daily artifacts with inertia sensors

Monitoring motor symptoms in Parkinson’s disease via instrumenting daily artifacts with inertia sensors

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